Algorithms, data, and platforms: the diverse challenges of governing AI

Artificial intelligence (AI) poses a set of interwoven challenges. A new general purpose technology likened to steam power or electricity, AI must first be clearly defined before considering its global governance. In this context, a useful definition is technology that uses advanced computation to perform at human cognitive capacity in some task area. Like electricity, AI cannot be governed in isolation, but in the context of a broader digital technology toolbox. Establishing national and community priorities on how to reap AI’s benefits, while managing its social and economic risks, will be an evolving debate. A fundamental driver of the development and deployment of AI tools, of the algorithms and data, are the dominant Digital Platform Firms (DPFs). Unless specifically regulated, DPF's set de facto rules for use of data and algorithms. That can shift the borderline between public and private, and result in priorities that differ from those of the public sector or civil society. Governance of AI and the toolbox is a critical component of national success in the coming decades, as governments recognize opportunities and geopolitical risks posed by the suite of technologies. However, AI pries open a Pandora's box of questions that sweep across the economy and society engaging diverse communities. Rather than strive towards global agreement on a single set of market and social rules, one must consider how to pursue objectives of interoperability amongst nations with quite different political economies. Even such limited agreements are complicated following the Russian invasion of Ukraine.